Small Table to Large Table Join — Solution & ExplanationProblems / Small Table to Large Table Join / EditorialApproachThis problem demonstrates the dimension-fact join pattern:

Start from the large table (sales, 300 rows) and join the small table (categories, 7 rows).

Compute derived columns — revenue and tax for each row.

Aggregate by category.

Why This MattersIn distributed systems (Spark, Presto, BigQuery), joining a small table to a large one uses a broadcast join — the small table is sent to every node, avoiding expensive shuffles of the large table. Understanding which table is small vs. large helps you:

Structure queries for better join strategies

Know when to use broadcast hints

Avoid accidentally shuffling billion-row tables

Complexity

O(n) scan of the large table with O(1) lookups into the small hash table, plus a single-pass aggregation.

Hints

Start from the large sales table and join the small categories table to it.

Compute revenue as quantity * unit_price, then multiply by tax_rate for tax.

In distributed systems, the small table would be broadcast to avoid shuffling the large table.

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